Senior Manager, Data Science

In this role you will define and lead AI and data science strategy across ML, NLP, search, and generative AI to deliver impactful, scalable solutions. You will guide teams through the full lifecycle of AI systems, from experimentation to production, while aligning work to product goals and customer needs. You will influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation. This role supports products and education initiatives within a global healthcare and clinical learning context, contributing to science advancement and health improvement at scale. Join a collaborative, quality-focused team that values trust and agility, and help shape responsible,

• healthy work/life balance
• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals

• Define AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI aligned with product goals and business priorities
• Lead and develop high-performing teams through coaching, prioritization, scientific rigor, and inclusive culture
• Deliver advanced AI and knowledge-discovery systems across the full lifecycle (experimentation to production), including LLMs, RAG, search, and domain-enriched solutions
• Establish robust evaluation frameworks, metrics, experimentation practices, and responsible AI standards
• Influence product, technology, and business by partnering with cross-functional leaders, shaping roadmaps, translating insights, and aligning teams on impact

• Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or related quantitative field or equivalent practical experience
• Strong technical expertise across modern data science methods including ML, experimentation, deep learning, generative AI, and production AI systems
• Hands-on experience delivering AI-powered products (LLMs, RAG, semantic search, embeddings, agentic workflows, knowledge-driven systems)
• Proven success leading and developing technical teams in complex product, platform, or research environments
• Experience with large, complex datasets and building scalable, production-ready AI/ML systems
• Strong people leadership, prioritization, communication, and stakeholder management; ability to turn ambiguity into clear strategy and measurable outcomes

• leadership
• communication
• stakeholder management
• machine learning
• experimentation
• deep learning